73 citations · 585 across the 58 of their papers we have counts for
4 papers · 1 filter
Differential Privacy for the Analyst via Private Equilibrium Computation
Justin Hsu, Aaron Roth, Jonathan Ullman
We give new mechanisms for answering exponentially many queries from multiple analysts on a private database, while protecting differential privacy both for the individuals in the…
Answering n^{2+o(1)} Counting Queries with Differential Privacy is Hard
Jonathan Ullman
A central problem in differentially private data analysis is how to design efficient algorithms capable of answering large numbers of counting queries on a sensitive database. Coun…
Mechanism Design in Large Games: Incentives and Privacy
Michael Kearns, Mallesh M. Pai, Aaron Roth +1
We study the problem of implementing equilibria of complete information games in settings of incomplete information, and address this problem using "recommender mechanisms." A reco…
Faster Algorithms for Privately Releasing Marginals
Justin Thaler, Jonathan Ullman, Salil Vadhan
We study the problem of releasing -way marginals of a database , while preserving differential privacy. The answer to a -way marginal query is the fracti…